Evaluation of anti-hyperglycemic activities of phloridzin in diabetic mice

Background: The aim of the study was to investigate the hypoglycemic effects of Phloridzin.Methods and Materials: High fat diet induced diabetic KKAy mice were administered with phloridzin at an oral dose (60 mg/kg/day, ig.) for 10 weeks. A range of parameters, including blood glucose and lipid, serum insulin, glucose tolerance, were tested to evaluate its anti-hyperglycemic effects.Results: Phloridzin decreased water-intake, body weight, FBG, FINS, HOME-IR, Serum leptin, and CRP levels, increased serum adiponectin level in diabetic mice. Phloridzin also improved the oral glucose tolerance test (OGTT) to a certain degree. In addition, phloridzin decreased liver index, and epididymal, perirenal white adipose tissue indexs, increased pancreas index in diabetic mice. At last, phloridzin increased hepatic GK activity and hepatic glycogen level, decreased hepatic PEPCK, G-6-Pase activities in diabetic mice.Conclusions: Phloridzin possessed anti-hyperglycemic activities.Keywords: Diabetes, Phloridzin, FBG, Insulin resistance, Area under curv

An experimental study on biased cognitive processing in accidentally injured patients with different posttraumatic growth levels

Background: Various studies have assessed the negative and/or positive changes in the aftermath of traumatic events. Accidental injuries (such as accidents, injuries, etc.), for its high incidence and disability rate, is easy to cause serious psychological problems and hinder the physical and psychological rehabilitation of the patients.Material and Methods: To explore the characteristics of attention bias in accidentally injured patients with different levels of Posttraumatic growth (PTG), total score of PTG was adopted to screen out 15 high-PTG group and low-PTG group respectively among accidentally injured patients. Dot probe task was used with positive, negative and neutral facial expression pictures as experimental materials. An experimental design of 2 (facial expression: positive and negative)×2 (consistency of probe point and facial expression: consistent and inconsistent)×2 (PTG level: high and low) was employed.Results: Patients with low PTG level had attention bias toward the negative emotional stimuli, and difficulty in distraction from the negative emotional pictures. The value of D and DI were both significantly greater than 0 (p<0.05). Patients with high PTG level did not demonstrate significant attention bias toward positive or negative emotional stimuli. The responding time of patients with high PTG level was significantly shorter than that in patients with low PTG level in the incongruent task (p<0.05).Conclusion: There are different characteristics of implicit cognitive processing in patients with different level of PTG, suggesting the necessity of psychological intervention on the accidentally injured patients.Keywords: Accidentally injured patients; Posttraumatic growth; Attention bias; Dot probe tas

Properties of charge transport in a novel holographic quantum phase transition model

We study the properties of charge transport in a novel holographic QPT (quantum phase transition) model, which has two different metallic phases: the normal metallic phase and the novel metallic one. We numerically work out the scaling behaviors of DC (direct current) resistivity at low temperatures in both different metallic phases. The numerical results are solidly in agreement with the analytical ones determined by the near horizon geometry. Then, we mainly explore the properties of the low-frequency AC (alternating current) conductivity. A remarkable characteristic is that the normal metallic phase is a coherent system with vanishing intrinsic conductivity $\sigma_Q$, which is independent of the strength of the momentum dissipation. This result is in contrast with the common belief that with the strength of the momentum dissipation increasing, the system changes from a coherent phase to an incoherent one. But the novel metallic phase is an incoherent system with non-vanishing $\sigma_Q$. Away from the QCP (quantum critical point), $\sigma_Q$ increases, which indicates that the incoherent behavior becomes stronger.Comment: 16 pages, 5 figure

Diagnosing quantum phase transition via holographic entanglement entropy at finite temperature

We investigate the behavior of the holographic entanglement entropy (HEE) in proximity to the quantum critical points (QCPs) of the metal-insulator transition (MIT) in the Einstein-Maxwell-dilaton-axions (EMDA) model. Due to the fact that the ground state entropy density of the EMDA model is vanishing for insulating phase, but non-vanishing for the metallic phase, we used to expect that it is the HEE itself that characterizes the QCPs. This expectation is validated for certain case, however, we make a noteworthy observation: for a specific scenario, it is not the HEE itself but rather the second-order derivative of HEE with respect to the lattice wave number that effectively characterizes the quantum phase transition (QPT). This distinction arises due to the influence of thermal effects. These findings present novel insights into the interplay between HEE and QPTs in the context of the MIT, and have significant implications for studying QPT at finite temperatures.Comment: 15 pages, 5 figure

Identification and pharmacokinetics of saponins in Rhizoma Anemarrhenae after oral administration to rats by HPLC-Q-TOF/MS and HPLC-MS/MS

Rhizoma Anemarrhenae is a well-known herbal medicine with saponins as its commonly regarded major bioactive components. It is essential to classify the properties of saponins which are associated with their toxicity and efficacy. In this study, 25 compounds were identified by HPLC-Q-TOF/MS in the extract of Rhizoma Anemarrhenae and 8 saponins were detected in rat plasma by HPLC-MS/MS after oral administration of this extract. These were neomangiferin, mangiferin, timosaponin E1, timosaponin E, timosaponin B-II, timosaponin B-III, timosaponin A-III and timosaponin A-I. A sensitive and accurate HPLC-MS/MS method was developed and successfully applied to a pharmacokinetic study of the abovementioned eight saponins after oral administration of the Rhizoma Anemarrhenae extract to rats. The method validation, including specificity, linearity, precision, accuracy, recovery, matrix effect and robustness, met the requirements of the intended use. The pharmacokinetic parameter, Tmax value, ranged from 2 to 8 h for these eight saponins whereas their elimination half-life (t1/2) ranged from 4.06 to 9.77 h, indicating slow excretion. The plasma concentrations of these eight saponins were all very low, indicating a relatively low oral bioavailability. All these results provide support for further clinical studies

Point Cloud Pre-training with Diffusion Models

Pre-training a model and then fine-tuning it on downstream tasks has demonstrated significant success in the 2D image and NLP domains. However, due to the unordered and non-uniform density characteristics of point clouds, it is non-trivial to explore the prior knowledge of point clouds and pre-train a point cloud backbone. In this paper, we propose a novel pre-training method called Point cloud Diffusion pre-training (PointDif). We consider the point cloud pre-training task as a conditional point-to-point generation problem and introduce a conditional point generator. This generator aggregates the features extracted by the backbone and employs them as the condition to guide the point-to-point recovery from the noisy point cloud, thereby assisting the backbone in capturing both local and global geometric priors as well as the global point density distribution of the object. We also present a recurrent uniform sampling optimization strategy, which enables the model to uniformly recover from various noise levels and learn from balanced supervision. Our PointDif achieves substantial improvement across various real-world datasets for diverse downstream tasks such as classification, segmentation and detection. Specifically, PointDif attains 70.0% mIoU on S3DIS Area 5 for the segmentation task and achieves an average improvement of 2.4% on ScanObjectNN for the classification task compared to TAP. Furthermore, our pre-training framework can be flexibly applied to diverse point cloud backbones and bring considerable gains

Aplikasi Image Thresholding Untuk Segmentasi Objek

Salah satu operasi di dalam analisis citra adalah segmentasi citra, yaitu memisahkan objek dari latar belakangnya atau dari objek lain yang tidak menjadi perhatian. Metode sementasi yang sederhana adalah dengan operasi pengambangan (thresholding). Operasi pengambangan menghasilkan citra biner, yang dalam hal ini objek yang diacu di-set berwarna putih sedangkan latar belakangnya di-set berwarna hitam (atau sebaliknya bergantung kasusnya). Makalah ini mempresentasikan penggunaan operasi pengambangan untuk melakukan segmentasi objek. Eksperimen dilakukan dengan menggunakan kakas MATLAB. Hasil eksperimen memperlihatkan bahwa pemilihan nilai ambang (threshold) yang tepat sangat menentukan keberhasilan segmentasi